QuantumFoam is a layered, manifold-centric quantum foam signal inference and analysis toolkit.
- High-throughput, compliance-driven, multi-source signal analytics
- Quantum Foam Inference Metric (QFIM) calculation
- Real-time anomaly detection and streaming analysis
- Device abstraction for high-frequency recording/streaming
- Robust storage and metadata management
- Modular, extensible architecture for advanced research or field deployment
quantumfoam/ quantumfoam/ # Core Python modules examples/ # Usage and demonstration scripts tests/ # Unit and integration tests storage/ # Data, features, metadata, archives cloudsync/ # Placeholder for cloud sync integration logs/ # Logging and audit trails .gitignore README.md LICENSE setup.py pyproject.toml
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- Install dependencies
pip install numpy scipy matplotlib soundfile pyyaml
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- Run an example
python examples/example_qfim.py
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- Develop your own modules and models
- Start with the stubs in
quantumfoam/ - Store audio and analysis results in
/storage - Log events in
/logs
- Designed for high-integrity, research-grade or operational use
- All data operations can be routed through
storage/ - Default settings are provided in
config.py - Extend for quantum-safe or FIPS-compliant storage as needed
MIT (or your chosen license—edit LICENSE file)
© 2025 QuantumFoam Contributors. All rights reserved.